RNA-Seq of CD3+ T cells flow sorted from MLR assays with TNF/TNFR inhibitory compound combination treatments
RNA-seq (gene expression) · human · 64 samples
- What it is
- RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
- Organism
- Homo sapiens (human)
- Samples
- 64 samples: 64 samples, each with a distinct title — no replicated groupsGroups are read from the sample names, not from the paper. Check the list below.
- Data you can get
- A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.
Processed table
The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE339038_RAW.tar (it can run to tens of gigabytes).
Raw sequencing reads
The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.
What the files usually look like: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.
Also filed as BioProject PRJNA1496849 and SRA study SRP718916. Searching any of these in the dataset finder brings you back here.
Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.
How we read this: Read from 64 sample titles: 64 distinct titles with little repetition. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.
- GSM9887309 Unstim_Donor A
- GSM9887310 Amlite + IgG1_Donor A
- GSM9887311 Unstim_Donor B
- GSM9887312 Amlite + IgG1_Donor B
- GSM9887313 Unstim_Donor C
- GSM9887314 Amlite + IgG1_Donor C
- GSM9887315 Unstim_Donor D
- GSM9887316 Amlite + IgG1_Donor D
- GSM9887317 No drug_Donor A
- GSM9887318 Bam + IgG1_Donor A
- GSM9887319 No drug_Donor B
- GSM9887320 Bam + IgG1_Donor B
- GSM9887321 No drug_Donor C
- GSM9887322 Bam + IgG1_Donor C
- GSM9887323 No drug_Donor D
- GSM9887324 Bam + IgG1_Donor D
- GSM9887325 IgG1+IgG1_Donor A
- GSM9887326 Ada + Dapiro_Donor A
- GSM9887327 IgG1+IgG1_Donor B
- GSM9887328 Ada + Dapiro_Donor B
- GSM9887329 IgG1+IgG1_Donor C
- GSM9887330 Ada + Dapiro_Donor C
- GSM9887331 IgG1+IgG1_Donor D
- GSM9887332 Ada + Dapiro_Donor D
- GSM9887333 IgG1+IgG4_Donor A
- GSM9887334 Ada + Amlite_Donor A
- GSM9887335 IgG1+IgG4_Donor B
- GSM9887336 Ada + Amlite_Donor B
- GSM9887337 IgG1+IgG4_Donor C
- GSM9887338 Ada + Amlite_Donor C
- GSM9887339 IgG1+IgG4_Donor D
- GSM9887340 Ada + Amlite_Donor D
- GSM9887341 Ada + IgG1_Donor A
- GSM9887342 Dapiro + Amlite_Donor A
- GSM9887343 Ada + IgG1_Donor B
- GSM9887344 Dapiro + Amlite_Donor B
- GSM9887345 Ada + IgG1_Donor C
- GSM9887346 Dapiro + Amlite_Donor C
- GSM9887347 Ada + IgG1_Donor D
- GSM9887348 Dapiro + Amlite_Donor D
+ 24 more — browse all 64 samples with per-sample file links →
- GSE317789 Single-cell and spatial profiling reveal cDC2A-CXCL13+ CD8+ T-epithelial cell crosstalk and cytotoxicity through TNFRSF9 in cutaneous and mucosal lichen planus 42 samples shares tnfr, tnf
- GSE328951 The embryonic origins of site-specific arthritis; Bulk RNA sequencing of CD34+(Pi16+) fibroblasts stimulated with TNF and IL1b. 24 samples shares cd3, tnf
- GSE274135 NANP Targeting Radio-sensitizes Glioblastoma through TNFR1 Sialylation-Driven Mesenchymal Shift 10 samples shares tnfr, tnf
- GSE176189 Integrative single-cell and spatial transcriptomic analyses identify a pathogenic cholangiocyte niche and TNFRSF12A as therapeutic target for biliary atresia 36 samples shares tnfr, tnf
- GSE305979 Perturbational single-cell RNA-seq time course of CD34+ HSPC megakaryocyte differentiation with CMO multiplexing (Days 0–7, 1 uM compounds) 34 samples shares cd3, compound
- GSE270661 Characterisation of the regulatory landscape in Crohn’s disease reveals miRNA-associated alterations that shape anti-TNF response (CIBER-120) 119 samples shares tnf
- GSE215045 Transcriptional profiling by 3' digital gene expression of human CD34+ HSPCs isolated from the umbilical cord blood 96 samples shares cd3
- GSE283710 RSK1 is an exploitable dependency in myeloid malignancies [CD34RNAseq] 90 samples shares cd3
Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.